DeepSeek Harness Released in Developer Preview as Open-Source Agent Runtime
DeepSeek AI has released DeepSeek Harness (dsh) in developer preview along with its open-source repository. It is a local agent runtime built around a plugin-first architecture to orchestrate AI agent workflows. By providing an open-source scaffolding for tools, memory, sandboxes, and loops, DeepSeek Harness simplifies running autonomous agents locally. It lowers the barrier for developers to build modular extensions for large language model applications. DeepSeek Harness utilizes an 'everything-is-a-plugin' architecture powered by Cordis, providing modular plugins for models, sessions, storage, and scheduling. The early developer preview is released on GitHub as version 0.1.2-rc.1.
## BACKGROUND
An AI agent harness (also called agent scaffolding) is the software infrastructure surrounding a Large Language Model (LLM) that enables it to operate as an active agent. It manages tool execution, state persistence, memory, and sandbox environments outside of the core LLM weights.